{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:43:43Z","timestamp":1740120223487,"version":"3.37.3"},"reference-count":22,"publisher":"World Scientific Pub Co Pte Ltd","issue":"04","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61403232"],"award-info":[{"award-number":["61403232"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61327003"],"award-info":[{"award-number":["61327003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Shandong Province, China","award":["ZR2014FQ025"],"award-info":[{"award-number":["ZR2014FQ025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2019,4]]},"abstract":"<jats:p> To address the problem that many existing approaches are not appropriate for action recognition in low-resolution (LR) videos, this paper presents a framework based on the Dempster\u2013Shafer (DS) theory for this purpose. In the framework, artificial neural networks (ANNs) are firstly trained for every class with training samples, and then basic belief assignments (BBAs) for underlying classes are computed with the trained ANNs. The resulted BBAs are fused from all frames in the whole video sequentially by frame-by-frame based on DS\u2019s rule of fusion. Action recognition is last performed with a threshold-based decision making. We conducted experiments on extensive testing data with various levels of video resolution. Results reveal that the proposed framework: (1) shows outperforming recognition performances compared with state-of-the-art classifications, respectively, such as sequence matching, voting-based strategy and bag-of-words (BoW) method; and (2) can achieve a low observational latency in recognition. <\/jats:p>","DOI":"10.1142\/s0218001419560020","type":"journal-article","created":{"date-parts":[[2018,8,13]],"date-time":"2018-08-13T05:38:00Z","timestamp":1534138680000},"page":"1956002","source":"Crossref","is-referenced-by-count":1,"title":["Recognizing Human Actions in Low-Resolution Videos: An Approach Based on the Dempster\u2013Shafer Theory"],"prefix":"10.1142","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6892-0706","authenticated-orcid":false,"given":"Zhen","family":"Gao","sequence":"first","affiliation":[{"name":"Key Laboratory of High-efficiency and Clean Mechanical Manufacture of MOE, National Demonstration Center for Experimental Mechanical Engineering Education, School of Mechanical Engineering, Shandong University, Jinan, P. 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